A new method to find neighbor users that improves the performance of Collaborative Filtering
作者：
Highlights：
• We propose a new neighbors finding method for CF based on subspace clustering.
• Based on subspaces, tree structures of neighbor users are drawn for the target user.
• Proposed method finds the best neighbors without any adjustable parameters.
• A new similarity method is proposed to compute the similarity value.
• Proposed method has been tested by Movielens 100K, Movielens 1M and Jester datasets.
摘要
•We propose a new neighbors finding method for CF based on subspace clustering.•Based on subspaces, tree structures of neighbor users are drawn for the target user.•Proposed method finds the best neighbors without any adjustable parameters.•A new similarity method is proposed to compute the similarity value.•Proposed method has been tested by Movielens 100K, Movielens 1M and Jester datasets.
论文关键词：Recommender System,Collaborative Filtering,Sparsity,High dimensionality,Subspace clustering,Neighbor users
论文评审过程：Received 28 November 2016, Revised 13 April 2017, Accepted 14 April 2017, Available online 14 April 2017, Version of Record 22 April 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.04.027
